{"id":3531048,"url":"https://alion.io/job/rocket-companies-software-engineer-ii-python-ai-engineer","title":"Software Engineer II - Python AI Engineer","company":{"id":1967610,"name":"Rocket Companies","domain":"rocket.com","url":"https://alion.io/company/rocket-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":104,"ghost_share":0,"stale_share":0.904,"repost_share":0,"time_to_fill_p50_days":36,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Detroit, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":98000,"max_usd":189000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":508},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"LangGraph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Agile","optional":true},{"name":"Amazon CloudWatch","optional":true},{"name":"Amazon ECS","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Amazon EventBridge","optional":true},{"name":"Amazon S3","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"Anthropic","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Lambda","optional":true},{"name":"AWS Step Functions","optional":true},{"name":"FastAPI","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LLM","optional":true},{"name":"OpenAI","optional":true},{"name":"RAG","optional":true},{"name":"Splunk","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-30T16:02:57Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-10-31T02:13:55Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"As a Python AI Engineer on our Data Science/AI Platform team, you will be at the forefront of our most ambitious technical initiatives. Your role is dual-purposed: you will build and orchestrate next-generation Agentic AI systems using AgentCore and LangGraph, and you will act as a Machine Learning Engineer (MLE) to productionize the sophisticated models developed by our Data Scientists.\nWe don't just follow industry trends; we aim to set them. You will be expected to be a perpetual student of the field, constantly researching and implementing the newest technologies to ensure our platform remains world-class.\nMinimum Qualifications\nMaster's degree in Computer Science, Software Development, Machine Learning, or a related field, OR equivalent professional experience (3-5+ years in production-level engineering).\nExpert-level proficiency in Python with a focus on building distributed, scalable cloud-native services.\nProven experience in a Data Science or Machine Learning environment, specifically in bridging the gap between research code and production software.\nPreferred Qualifications\nAgentic AI & Orchestration:\nHands-on experience with AgentCore runtime for building and managing autonomous agents.\nExtensive experience using LangGraph to create complex, stateful multi-agent orchestrations with high visibility.\nDeep familiarity with Amazon Bedrock, OpenAI, or Anthropic APIs and the latest advancements in LLM reasoning.\nExperience building and optimizing RAG (Retrieval-Augmented Generation) pipelines.\nMachine Learning Engineering (MLE):\nProven track record of productionizing Data Science models, transforming research-grade code into high-performance, scalable APIs (e.g., using FastAPI).\nExperience with the full MLOps lifecycle: model deployment, versioning, and performance monitoring.\nFamiliarity with Amazon SageMaker or other cloud-based ML platforms.\nCloud & Infrastructure (AWS):\nExpertise in the AWS ecosystem: Lambda (Serverless), Step Functions, ECS/EKS (Containers), EventBridge, and S3.\nStrong proficiency in Infrastructure as Code (IaC) using Terraform.\nExperience building asynchronous, event-driven architectures.\nObservability & Engineering Excellence:\nProficiency in Splunk and CloudWatch for production monitoring and alerting.\nStrong knowledge of software development life cycle (SDLC) processes, including unit testing, regression testing, and Agile concepts.\nAbility to work with broad, loosely developed concepts and translate them into precise technical specifications.\nKey Responsibilities\nAgentic AI Innovation: Design and implement autonomous agents using AgentCore and orchestrate them via LangGraph to ensure complex workflows are visible and manageable.\nMLE Productionization: Partner with Data Scientists to take ML models from research notebooks into scalable, production-ready AWS environments.\nConstant Research: Proactively research, test, and present the newest technologies, frameworks, and AI research papers to the team. You are expected to be an early adopter of tools that can improve our velocity or service quality.\n System Architecture: Build and maintain the cloud-native infrastructure (AWS) required for AI/ML inference and agentic execution, ensuring high availability and cost-efficiency.\nObservability: Implement deep monitoring and alerting for all services, using LangGraph for agent-specific visibility and Splunk for broader system health.\nCode Quality: Participate in rigorous code reviews and help define the engineering standards for the Data Science team.\nCollaboration: Work without complete specifications to help derive technology solutions that meet the evolving needs of the business.\nWhat you’ll get\nOur team members fuel our strategy, innovation and growth, so we ensure the health and well-being of not just you, but your family, too! We go above and beyond to give you the support you need on an individual level and offer all sorts of ways to help you live your best life. We are proud to offer eligible team members perks and health benefits that will help you have peace of mind. Simply put: We’ve got your back. Check out our full list of Benefits and Perks.\nOn-Call Expectations\nThis role may include participation in an on-call rotation to support production systems and ensure service reliability. On-call responsibilities may include coverage during nights and weekends. If applicable, frequency and scheduling will be determined by team needs and communicated accordingly.\nAbout us\nRocket Close is a leading national provider of title insurance, property valuations and settlement services. Here, you’ll be given all the resources and support needed to deliver innovative solutions and in turn, your hard work will be rewarded with a competitive compensation package and an array of other amazing benefits. Apply today to join a team that offers career growth, amazing benefits and the chance to work with leading industry professionals.\nThis job description is an outline of the primary responsibilities of this position and may be modified at the discretion of the company at any time. Decisions related to employment are not based on race, color, religion, national origin, sex, physical or mental disability, sexual orientation, gender identity or expression, age, military or veteran status or any other characteristic protected by state or federal law. The company provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable state and federal laws. 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